Report · AI & Tech

Americans are divided over teachers using AI for assignments

Reading

Americans tilt toward trusting teachers with the technology: 47% agree that educators can successfully use AI to build assignments for their students, including 10% who strongly agree, according to a May 2026 Verasight survey.

Opinion fractures from there, as 27% disagree, 14% of them strongly, and 26% neither agree nor disagree.

Topline

response scale

Topline scale

Americans are divided over teachers using AI for assignments.

Faculty/educators/teachers can successfully use artificial intelligence (AI) to develop assignments for their students?

  • Somewhat agree 36.8%
  • Neither disagree nor agree 25.6%
  • Strongly disagree 14.2%
  • Somewhat disagree 13.0%
  • Strongly agree 10.4%

2026 · base n 1,000 · +/- 3.3%

beliefs

View source

Methodology

Full methodology
Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting
Field dates
2026-05-11 → 2026-05-11
Base (unweighted)
1,000
Margin of error
+/- 3.3%
Module
beliefs

Source

Citation

Verasight SPSP Omnibus Survey #2026-045, fielded May 11-11, 2026, N=1,000 US adults age 18+, +/- 3.3%.

https://reports.verasight.io/r/spsp26

Verasight survey methodology

How Verasight conducts surveys.

This page describes the Verasight general survey contract, separate from how the Data Library packages it. When a wave report is published, its field dates, sample sizes, and module breakdown are listed in that report.

Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting.
Population
US adults age 18+.
Sample design
Surveys are run as omnibus or single-topic waves. Omnibus waves are split into modules with their own respondent set, typically around one thousand respondents per module.
Field window
Each wave specifies its own field dates. Most omnibus waves field across roughly two weeks.
Weighting
Per-module weighting to CPS targets including age, race and ethnicity, sex, income, education, region, and metropolitan status.
Partisanship benchmark
Pew Research Center's NPORS benchmarking surveys, three-year running average.
Vote benchmark
2024 presidential vote population benchmarks.
Margin of error
Typically about plus or minus 3.4 to 3.6 percent per module at standard module sizes. Question-level MoE is recomputed when a base shrinks materially below the module baseline.
Reporting
The canonical report hub is reports.verasight.io. Verified legacy reports remain on their original hosts, and unpublished reports are marked pending.
Transparency
Verasight is a member of the American Association for Public Opinion Research Transparency Initiative.

The canonical report hub is reports.verasight.io; older reports may remain on verified legacy hosts.